Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer

Background: Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine. Methods: Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs). A retrospective cohort (BC = 66 and CTRL = 50) and RT-qPCR were used to confirm the selected differently expressed miRNAs. Diagnostic accuracy was assessed using machine learning algorithms (logistic regression, naive Bayes, and random forest), which were trained to discriminate between BC and CTRL, using as input either miRNAs, SERS, or both. The molecular stratification of BC based on miRNA and SERS profiling was performed to discriminate between high-grade and low-grade tumors and between luminal and basal types. Results: Combining SERS data with three differentially expressed miRNAs (miR-34a-5p, miR-205-3p, miR-210-3p) yielded an Area Under the Curve (AUC) of 0.92 +/- 0.06 in discriminating between BC and CTRL, an accuracy which was superior either to miRNAs (AUC = 0.84 +/- 0.03) or SERS data (AUC = 0.84 +/- 0.05) individually. When evaluating the classification accuracy for luminal and basal BC, the combination of miRNAs and SERS profiling averaged an AUC of 0.95 +/- 0.03 across the three machine learning algorithms, again better than miRNA (AUC = 0.89 +/- 0.04) or SERS (AUC = 0.92 +/- 0.05) individually, although SERS alone performed better in terms of classification accuracy. Conclusion: miRNA profiling synergizes with SERS profiling for point-of-care diagnostic and molecular stratification of BC. By combining the two liquid biopsy methods, a clinically relevant tool that can aid BC patients is envisaged

Improving the Adherence to Antiretroviral Therapy, a Difficult but Essential Task for a Successful HIV Treatment—Clinical Points of View and Practical Considerations

HIV infection is responsible for one the most devastating human pandemics. The advent of antiretroviral therapy has changed the course of the pandemic and saved millions of lives. Complex therapeutic regimens have been introduced since 1996 and have contributed to the transformation of HIV infection into a treatable chronic diseases. New types of potent antiretrovirals and their combinations, including “once daily” treatment, have simplified the regimens and diminished side effects. Nevertheless the adherence to antiretroviral therapy remains unsatisfactory and varies between 27 and 80% across different population in various studies, compared with the required level of 95%. The lack of adherence to antiretroviral therapy is a multi-factorial and dynamic process which raises considerable difficulties for long-term follow-up. Current solutions to this problem are complex. These should be applied by a multidisciplinary team and should take into account key features related to both the individual and social factors as well as to the population to whom it belongs (children, teenagers, elderly, marginalized population like drug users, incarcerated patients, sex workers, etc.). Importantly, adherence should continue to be monitored even in patients known to be compliant. In case of subsequent failure the team should identify the reasons for non-adherence and apply the appropriate methods. Where usual methods have no chance of success, a coordinated package of services also known as “harm reduction” can be offered in order to reduce the risks of transmission. The current article analyses the concept of adherence to antiretroviral therapy, the shortcomings of this medication and the methods that can be applied in practice to increase adherence. Emphasis is placed on the analysis of groups at high risk for HIV infection that currently represent the spearhead with which the HIV pandemic is spreading

Physiological effects induced by the hydroalcoholic extract of Violae tricoloris herba (wild pansy aerial parts) on Triticum aestivum L

Wild pansy (Viola tricolor) hydroalcoholic extract was prepared by extraction of powdered dried – flowering aerial parts with ethanol 70% v/v (1:10), by reflux for two hours. This was diluted with distilled water to give the final concentrations of 0.5, 1.0 and 5% (v/v) (VTEx1, VTEx2 and VTEx3). These extracts were tested for their effects on seed germination and seedlings growth of wheat (Triticum aestivum) in a laboratory experiment. Distilled water was used as a control (C). After the 10 days of experiment, we evaluated seed germination of wheat and seedlings growth (roots and shoots lengths, their fresh and dry biomass)

SERS Liquid Biopsy Profiling of Serum for the Diagnosis of Kidney Cancer

Renal cancer (RC) represents 3% of all cancers, with a 2% annual increase in incidence worldwide, opening the discussion about the need for screening. However, no established screening tool currently exists for RC. To tackle this issue, we assessed surface-enhanced Raman scattering (SERS) profiling of serum as a liquid biopsy strategy to detect renal cell carcinoma (RCC), the most prevalent histologic subtype of RC. Thus, serum samples were collected from 23 patients with RCC and 27 controls (CTRL) presenting with a benign urological pathology such as lithiasis or benign prostatic hypertrophy. SERS profiling of deproteinized serum yielded SERS band spectra attributed mainly to purine metabolites, which exhibited higher intensities in the RCC group, and Raman bands of carotenoids, which exhibited lower intensities in the RCC group. Principal component analysis (PCA) of the SERS spectra showed a tendency for the unsupervised clustering of the two groups. Next, three machine learning algorithms (random forest, kNN, naïve Bayes) were implemented as supervised classification algorithms for achieving discrimination between the RCC and CTRL groups, yielding an AUC of 0.78 for random forest, 0.78 for kNN, and 0.76 for naïve Bayes (average AUC 0.77 ± 0.01). The present study highlights the potential of SERS liquid biopsy as a diagnostic and screening strategy for RCC. Further studies involving large cohorts and other urologic malignancies as controls are needed to validate the proposed SERS approach

Shear-Wave Elastography Variability Analysis and Relation with Kidney Allograft Dysfunction: A Single-Center Study

Shear-wave elastography (SWE) showed the absence or presence of significant differences among stable kidney allograft function and allograft dysfunction. We evaluated the variability of kidney allograft stiffness in relation to allograft dysfunction, respectively, in terms of a correlation of stiffness with patients’ characteristics. A single-center prospective study on patients who had undergone renal transplantation was conducted between October 2017 and November 2018. Patients were clinically classified as having a stable allograft function or allograft dysfunction. SWE examinations performed by the same radiologist with a LOGIQ E9 were evaluated. Ten measurements were done for Young’s modulus (kPa) at the level of allograft cortex and another ten at the level of medulla. Eighty-three SWE examinations from 63 patients, 69 stable allografts, and 14 allografts with dysfunction were included in the analysis. The intra-examinations stiffness showed high variability, with the quantile covariation coefficient ranging from 2.21% to 45.04%. The inter-examinations stiffness showed heterogeneity (from 28.66% to 42.38%). The kidney allograft cortex stiffness showed significantly higher values in cases with dysfunction (median = 28.70 kPa, interquartile range (IQR) = (25.68–31.98) kPa) as compared to those with stable function (median = 20.99 kPa, interquartile range = (16.08–27.68) kPa; p-value = 0.0142). Allograft tissue stiffness (both cortex and medulla) was significantly negatively correlated with body mass index (−0.44, p-value < 0.0001 for allograft cortex and −0.42, p-value = 0.0001 for allograft medulla), and positively correlated with Proteinuria/Creatinuria ratio (0.33, p-value = 0.0021 for allograft cortex and 0.28, p-value = 0.0105 for allograft medulla) but remained statistically significant only in cases with stable function. The cortical tissue stiffness proved significantly higher values for patients with allograft dysfunction as compared to patients with stable function, but to evolve as an additional tool for the evaluation of patients with a kidney transplant and to change the clinical practice, more extensive studies are needed